untitled - sdata201826.pdf

Data Descriptor:

A multi-year data

set on aerosol-cloud-precipitation-

meteorology interactions for

marine stratocumulus clouds

Armin Sorooshian

etal.

Airborne measurements of meteorological, aerosol, and stratocumulus cloud properties have been

harmonized from six

fi

eld campaigns during July-August months between

2005

and

2016

off the California

coast. A consistent set of core instruments was deployed on the Center for Interdisciplinary Remotely-

Piloted Aircraft Studies Twin Otter for

113

fl

ight days, amounting to

514

fl

ight hours. A unique aspect of

the compiled data set is detailed measurements of aerosol microphysical properties (size distribution,

composition, bioaerosol detection, hygroscopicity, optical), cloud water composition, and different

sampling inlets to distinguish between clear air aerosol, interstitial in-cloud aerosol, and droplet residual

particles in cloud. Measurements and data analysis follow documented methods for quality assurance. The

data set is suitable for studies associated with aerosol-cloud-precipitation-meteorology-radiation

interactions, especially owing to sharp aerosol perturbations from ship traf

fi

c and biomass burning. The

data set can be used for model initialization and synergistic application with meteorological models and

remote sensing data to improve understanding of the very interactions that comprise the largest

uncertainty in the effect of anthropogenic emissions on radiative forcing.

Design Type(s)

time series design

•

data integration objective

•

observation design

Measurement Type(s)

navigation data

•

atmospheric wind

•

pressure of air

•

temperature of air

•

cloud

•

particulate matter

•

nitric oxide

•

nitrogen dioxide

•

ozone

•

carbon monoxide

•

carbon dioxide

•

atmospheric water vapour

Technology Type(s)

GPS navigation system

•

data acquisition system

•

spectrometer

•

Particle

Count and Size Analyzer

Factor Type(s)

temporal_interval

Sample Characteristic(s)

North East Paci

fi

c Ocean

•

atmosphere

Correspondence and requests for materials should be addressed to A.S. (email: armin@email.arizona.edu).

A full list of authors and their af

fi

liations appears at the end of the paper.

OPEN

Received:

19

July

2017

Accepted:

4

January

2018

Published:

27

February

2018

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Background & Summary

Interactions among aerosol particles, meteorology, and warm clouds remain poorly understood yet

represent an area of intense research owing to their signi

fi

cance for the hydrological cycle, radiative

forcing, weather, visibility, and geochemical cycling of nutrients

. The representation of microphysical

and macrophysical processes relating aerosol particles, clouds, precipitation, dynamics, and thermo-

dynamics in current general circulation models relies on parameterizations that are highly uncertain

Barriers to calculating robustly these interactions include the wide range of length scales (~10

m) they

operate on, from a single particle to synoptic scale systems, the complexity of cloud systems and

associated feedbacks, the strong coupling between aerosol particles and meteorology, and the

inhomogeneous spatial distribution and short lifetime of particles

. While particles directly re

fl

ect and

absorb solar radiation, they indirectly in

fl

uence the planet

’

s energy balance via their role in modulating

cloud properties

–

. This indirect effect is linked to the largest source of uncertainty in estimates of the

total anthropogenic radiative forcing

. Furthermore, much of this uncertainty focuses on marine

stratocumulus clouds that exert a strong negative radiative effect and are the dominant cloud type based

on global area

Observational studies of stratocumulus clouds typically rely on some combination of surface, airborne,

and space-borne platforms, with each providing unique bene

fi

ts and limitations

. The primary links

between aerosol particles and clouds, and their coupling with thermodynamics and dynamics, occurs at

spatiotemporal scales ideal for aircraft

. One of the most signi

fi

cant challenges in the aerosol-cloud-

climate

fi

eld of research is untangling the effect of meteorology and aerosol particles on clouds

. This

requires extensive statistics to analyze how a perturbation in a single parameter of interest leads to a cloud

response, which involves holding other parameter values

fi

xed. For example, it is common to analyze

fi

eld

data at a

fi

xed value for a cloud macrophysical parameter such as cloud thickness or liquid water path

(LWP; see Table 1 for acronym and variable de

fi

nitions) with the aim of extracting a statistically

signi

fi

cant relationship between aerosol number concentration and a cloud property of interest, such as

cloud drop effective radius, cloud albedo, or precipitation rate

–

. However, even in these cases, it is

cautioned that statistical correlations cannot prove causality, and that synergistic inclusion of advanced

cloud models is required

While signi

fi

cant attention has been given to studying the effects of aerosol particles on clouds and

precipitation, an area of research that remains understudied with

fi

eld data is the effects of clouds and

precipitation on aerosol particles. Aerosol particles that enter a cloud either activate into cloud droplets or

exist as interstitial aerosol particles. As a result of collisions between interstitial particles and droplets,

coalescence among droplets and aqueous-phase chemistry in droplets modify the composition and size

distribution of particles in clouds, in turn, altering how particles interact with light and water vapor

Processing through collisions and coalescence alters only the number and size of aerosol particles, while

chemical processing affects their composition and size distribution as a result of aqueous-phase reactions

that produce low-volatility species that can remain in the aerosol phase after subsequent droplet

evaporation. Removal of particles via precipitation is important to understand, as it affects the spatial and

vertical distribution of aerosol particles, especially cloud condensation nuclei (CCN), in the atmosphere

Failure to account for wet scavenging effects on aerosol particles below clouds can bias investigations of

aerosol effects on clouds that rely on a measurement of sub-cloud aerosol

The goal of this work is to present a unique data set incorporating measurements from six

summertime aircraft campaigns focused on the northeastern Paci

fi

c Ocean where a persistent

summertime stratocumulus deck exists. The study region is an ideal natural laboratory for investigating

aerosol-cloud-precipitation-meteorology interactions due to strong aerosol perturbations from ship

emissions

and, sometimes, biomass burning. This data set is especially useful in efforts to improve

process-based understanding of cloud and precipitation formation by considering appropriate feedbacks

across sub-grid scales, that need to be understood to improve the spatial resolution of large-scale

models

Methods

Platform and Campaigns

The data set presented is based on measurements conducted with the Center for Interdisciplinary

Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter based out of Marina, California. Dates and

fl

ight

times are summarized in Table 2 (available online only) for each of the following six campaigns: the two

Marine Stratus/Stratocumulus Experiments (MASE I, MASE II), the Eastern Paci

fi

c Emitted Aerosol

Cloud Experiment (E-PEACE), the Nucleation in California Experiment (NiCE), the Biological and

Oceanic Atmospheric Study (BOAS), and the Fog and Stratocumulus Evolution Experiment (FASE). The

aircraft typically

fl

ew at ~55 m s

−

, with

fl

ights ranging from one hour to

fi

ve hours. The average take-off

and landing times were approximately 17:30 UTC (local time

UTC

–

7 h) and 21:30 UTC, respectively,

with the earliest take-off and latest landing being 14:38 UTC and 02:27 UTC, respectively. Flight tracks

for the 113

fl

ight days, which combine for 514 h of total

fl

ight time, are shown in Fig. 1. Of special note is

that during E-PEACE, an instrumented research vessel (R/V Point Sur) coordinated measurements of

aerosol and environmental parameters below the Twin Otter. The R/V Point Sur also executed controlled

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Acronym/Variable Name

fi

nition

AMS

Aerosol Mass Spectrometer

Black Carbon

BOAS

Biological and Oceanic Atmospheric Study

CAPS

Cloud, Aerosol, and Precipitation Spectrometer

CAS

Cloud and Aerosol Spectrometer

CCN

Cloud Condensation Nuclei

CDP

Cloud Droplet Probe

CIP

Cloud Imaging Probe

CIRPAS

Center for Interdisciplinary Remotely-Piloted Aircraft Studies

CPC

Condensation Particle Counter

C-ToF-AMS

Compact Time-of-Flight Aerosol Mass Spectrometer

CVI

Counter

fl

ow Virtual Impactor

DMA

Differential Mobility Analyzer

DMT

Droplet Measurement Technologies

E-PEACE

Eastern Paci

fi

c Emitted Aerosol Cloud Experiment

FASE

Fog and Stratocumulus Evolution Experiment

FSSP

Forward Scattering Spectrometer Probe

GPS

Global Positioning System

HiRes-ToF-AMS

High Resolution Time-of-Flight Aerosol Mass Spectrometer

Ion Chromatography

ICP-MS

Inductively Coupled Plasma Mass Spectrometry

ICP-QQQ

Triple Quadrupole Inductively Coupled Plasma Mass Spectrometry

INS

Inertial Navigation System

LPM

Liter Per Minute

LWC

Liquid Water Content

LWP

Liquid Water Path

MASE

Marine Stratus/Stratocumulus Experiment

NiCE

Nucleation in California Experiment

PBAP

Primary Biological Aerosol Particles

PCASP

Passive Cavity Aerosol Spectrometer Probe

PILS

Particle-Into-Liquid Sampler

PMS

Particle Measuring Systems

PSL

Polystyrene Latex Sphere

R/V

Research Vessel

Relative Humidity

SMPS

Scanning Mobility Particle Sizer

SP2

Single Particle Soot Photometer

SST

Skin Surface Temperature

TAS

True Aircraft Speed

UFCPC

Ultra

fi

ne Condensation Particle Counter

VOC

Volatile Organic Compound

WIBS

Waveband Integrated Bioaerosol Sensor

Particle Diameter

Cloud Droplet Number Concentration

Cloud Droplet Effective Radius

Virtual Temperature

θ

Potential Temperature

θ

Equivalent Potential Temperature

θ

Virtual Potential Temperature

Table 1.

fi

nitions of acronyms and variables.

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emissions of smoke from its deck to provide a unique identi

fi

able tracer signature. The cruise lasted from

12-23 July 2011; data from ship-borne measurements can be found elsewhere

Occasionally, up to three sub-

fl

ights were conducted that involved re-fueling at other sites or at

Marina. Such days are counted as a single

fl

ight in Table 2 (available online only) but are labeled with

extensions

‘

’

‘

’

, and

‘

’

for successive

fl

ights on a particular day. The objective of multi-

fl

ight days was

either to capture diurnally-relevant atmospheric features, or to sample in an area that extended outside

the range that one

fl

ight would allow.

Flight Strategies

The general

fl

ight strategy for sampling aerosol and clouds comprised the maneuvers shown in Figs 2 and

3, which excludes the transits between the measurement site and the Marina airport. When the aircraft

reached the area of interest after transits, it usually collected data along level legs at multiple altitudes

extending from near the ocean surface up to a few hundred meters above cloud top (Fig. 2a). Soundings

were conducted periodically throughout the

fl

ight in either a slant or spiral maneuver. As some

fl

ights

involved sampling at distances farther away from the coastline to the west or farther north/south as

compared to Marina, another

fl

ight strategy comprised stair-step patterns conducted repeatedly until the

aircraft turned back on a reverse course to repeat the maneuvers again until reaching the Marina airport

(Fig. 2b). Owing to the importance of ship emissions in the study region, the Twin Otter also executed

fl

ights paths to characterize the aerosol properties close to the ocean surface as depicted in Fig. 3, prior to

repeating the same patterns at higher levels in and above clouds. Data from such maneuvers are useful to

contrast the aerosol and cloud characteristics in and out of regions in

fl

uenced by plumes.

Instrument Descriptions

Table 3 summarizes the instruments used in each

fi

eld campaign along with corresponding size and time

resolution details. Below we describe the instruments in more detail. Additional guiding details about

using data from these instruments, including accuracy, precision, and working ranges can be found in the

‘

ReadMe.doc

’

fi

le accompanying the data set (Data Citation 1).

Navigational/Meteorological

Data are presented as a function of UTC time. Standard navigational and meteorological data are

provided at 1 Hz time resolution. For specialized analyses though, GPS and thermodynamic data can be

provided upon request with 10 and 100 Hz resolution, respectively. The Systron Donner C-MIGITS-III

GPS/INS system provided latitude, longitude, and altitude data. Pressure altitude was also determined by

use of measurements from a barometric pressure sensor (Setra Model 270). The pressure altitude

measured with the Setra sensor is based on static pressure measurements and assumes standard

atmosphere. The Setra sensor was plumbed to a static port on the aircraft that has been extensively

characterized for location error correction and for dependency on pitch angle and aircraft speed by use of

a trailing cone method

Four differential pressure transducers (Setra Model 239) and two barometric pressure transducers

(Setra Model 270), plumbed to a

fi

ve-hole radome gust probe provided measurements for determination

of turbulence and three dimensinoal winds. Horizontal and vertical winds were calculated from these

measurements in combination with platform velocity and altitude measurements provided by the

C-MIGITS-III GPS/INS system.

A Rosemount Model 102 total temperature sensor provided total temperature measurements, from

which ambient air temperature was calculated after taking into account dynamic heating and an

instrument-based recovery factor. Humidity data were obtained with an EdgeTech Vigilant chilled mirror

hygrometer (EdgeTech Instruments, Inc.). The measurement of dew point temperature by the Edgetech

chilled mirror dew point sensor was calibrated using a dew point generator (LI-COR, Inc.). Although not

provided, relative humidity (RH) can be calculated based on the ratio of the partial pressure of water

vapor relative to equilibrium vapor pressure, both of which are derived from measurements of

temperature and dew point temperature. Dew point temperature can be used to calculate speci

fi

humidity and water vapor mixing ratio. Furthermore, potential temperature (

θ

) can be calculated from

total temperature, while equivalent and virtual potential temperature (

θ

and

θ

), additionally require dew

point temperature in their calculation. Virtual temperature (

) can be calculated from total temperature

with a correction based on dew point temperature to eliminate the in

fl

uence of water vapor. Dry air

density can be calculated from total temperature and static pressure.

Earth

’

s skin surface temperature (SST) was measured using a nadir-facing infrared radiation

pyrometer (Heitronics KT 19.85). These measurements provide sea surface temperature when the

column below the aircraft is clear, or cloud top temperature when the aircraft is above clouds. The

pyrometer operates in an infrared spectral range where absorption by CO

and water vapor is minimal,

which minimizes errors in the surface temperature measurement.

True air speed (TAS) of the aircraft was determined using measurements of dynamic pressure and

temperature, the latter of which was corrected for the Mach number of the aircraft. Dynamic pressure

was obtained as the difference between total pressure (from center hole on radome) and static pressure

(from static port). An independent measurement of total pressure was also obtained from a pitot tube for

validation of the center hole pressure measurement.

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Inlets

Aerosol measurements during the

fi

eld campaigns were conducted with a forward-facing sub-isokinetic

inlet, which samples aerosol below 3.5

μ

m diameter with 100% ef

fi

ciency

. However, when in cloud,

some aerosol instruments were switched via a valve to sample downstream of a counter

fl

ow virtual

impactor (CVI) inlet. The CVI preferentially samples cloud droplets (rejecting smaller aerosol particles),

and then dries them to leave droplet-residue particles for downstream instruments to characterize.

During MASE I, the CVI employed was an early version

that was replaced starting in E-PEACE with a

new version offering higher sample

fl

ow rates from which an increased number of downstream

instruments could sample

. The previous and current version of the CVI had cutpoint sizes of

approximately 10 and 11

μ

m, respectively. Due to uncertainty in the transmission ef

fi

ciency of the CVI

inlet, data collected downstream of this inlet should be used only to assess relative rather than absolute

concentrations, i.e., to determine ratios of relevant parameters. In addition, during MASE II, a rear-facing

inlet was also employed in cloud to preferentially sample only interstitial aerosol (i.e., particles that did

not activate into cloud droplets). A summary of which instruments sampled downstream each of these

three inlets is provided in Table 4.

Cloud Measurements

Several cloud probes characterized the drop distribution from 0.5 to 1600

μ

m diameter. The Cloud,

Aerosol, and Precipitation Spectrometer (CAPS; Droplet Measurement Technologies, Inc.) is comprised

of the Cloud and Aerosol Spectrometer

(CAS;

–

μ

m) and the Cloud Imaging Probe (CIP;

~25

–

1600

μ

m). Only data from the forward scattering section of the CAS data (called CASF) are

reported. CAPS probe data are converted into size distributions, although it should be noted that the CAS

size exhibits considerable uncertainty in the 1-10

μ

m diameter range owing to in

fl

uence from Mie

resonances. The range of diameters in this size range can vary by a factor of two since drops having

different diameters produce similar scattered pulse heights. Data above 10

μ

m have reduced Mie

oscillation contamination, and their uncertainty drops signi

fi

cantly to ~30%

Other probes providing supporting measurements of drop distribution data included the Cloud

Droplet Probe

(CDP;

–

μ

m; Droplet Measurement Technologies (DMT), Inc.) and Forward

Scattering Spectrometer Probe (FSSP;

–

μ

m; Particle Measuring Systems (PMS), Inc., modi

fi

ed by

DMT, Inc.). The cloud probes were calibrated using standard methods including with monodisperse

polystyrene and glass beads. Past work has discussed uncertainties in counting and sizing associated with

these instruments

25,27,28

. CASF, CDP, and FSSP data are useful for quanti

fi

cation of cloud droplet

number concentration (

), droplet effective radius (

), liquid water content (LWC), and cloud optical

depth

, while the CIP is most useful for quanti

fi

cation of precipitation rates using documented methods,

such as those relating drop size and fall velocity

30,31

. Users should refer to literature to determine size

thresholds for cloud droplets versus drizzle droplets

32,33

. The number concentrations reported for each

size bin can be added to determine total drop concentrations from each probe across the size range of

interest. It is cautioned that the smallest bin channel for all probes is subject to uncertainty due to poorly

fi

ned lower and upper limit diameters for those bins.

The PVM-100 A probe

provides a separate measurement of LWC that does not require integrating

cloud drop size distributions. Cloud LWC is important for a number of other reasons, such as providing a

way to quantify cloud adiabaticity and cloud liquid water path (LWP)

, and identifying the cloud-base

and cloud-top, based on threshold values chosen by the data user

–

. However, users may instead prefer

to use the cloud probe data described previously to quantify values of the aforementioned cloud

properties. The sensitivity of the PVM-100 A probe decreases in drizzle, as it is designed to respond to

droplets smaller than 50

μ

. Thus, the use of LWC data requires caution for precipitating conditions.

Dissolved non-water constituents of cloud water were speciated and quanti

fi

ed using samples collected

with a modi

fi

ed Mohnen cloud water collector

. This collector was deployed in four of the six

campaigns, starting with E-PEACE. When in cloud, this slotted rod collector was manually extended out

of the top of the aircraft; samples were collected in high-density polyethylene bottles, typically for 5

–

min. Each liquid sample was then split into a number of fractions for different types of analyses: (i) pH

(Oakton Model 110 pH meter that was calibrated with 4.01 and 7.00 pH buffer solutions for E-PEACE,

NiCE, and BOAS; Thermo Scienti

fi

c Orion 8103BNUWP Ross Ultra Semi-Micro pH probe for FASE);

(ii) water-soluble ionic composition (Ion Chromatography, IC; Thermo Scienti

fi

c Dionex ICS

–

2100

system); and (iii) water-soluble elemental composition (Inductively Coupled Plasma Mass Spectrometry,

ICP-MS: Agilent 7700 Series for E-PEACE, NiCE, and BOAS; Triple Quadrupole Inductively Coupled

Plasma Mass Spectrometry (ICP-QQQ; Agilent 8800 Series) for FASE). Liquid concentrations were

converted into air-equivalent concentrations via multiplication with the average LWC during sample

collection.

Aerosol Measurements

Particle concentrations were recorded in each campaign using multiple condensation particle counters

(CPCs; TSI Inc.), speci

fi

cally a CPC 3010 (D

10 nm) and ultra

fi

ne CPC (UFCPC) 3025 (D

3 nm). The

saturation thresholds of these two CPCs are 10

and 10

−

, respectively; concentrations above those

limits are subject to coincidence errors, so use of such data is discouraged. Aerosol size distributions were

obtained in each campaign with a Passive Cavity Aerosol Spectrometer Probe (PCASP; PMS, Inc.,

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modi

fi

ed by DMT, Inc.; 0.1

–

2.6

μ

m) and a Scanning Mobility Particle Sizer (SMPS; ~ 10

–

800 nm), which

is comprised of a differential mobility analyzer (DMA; TSI Inc. Model 3081) coupled to a model 3010 TSI

CPC. Particle sizing by the SMPS was calibrated using polystyrene latex spheres (PSLs), while the PCASP

was calibrated with PSLs, water, and dioctyl sebacate. A reference CPC (TSI 3010) was used to calibrate

the concentration performance of both the SMPS and PCASP.

Submicrometer aerosol composition was measured with multiple instruments. The

fi

rst instrument

was the Aerosol Mass Spectrometer (AMS; Aerodyne Research Inc.), which quanti

fi

ed non-refractory

aerosol composition including sulfate, nitrate, ammonium, chloride, and organics

–

. A Compact Time-

of-Flight AMS (C-ToF-AMS) was used in MASE I, MASE II, E-PEACE, and NiCE, whereas a High

Resolution Time-of-Flight AMS (HiRes-ToF-AMS) was used in BOAS. At the entrance of the AMS, an

aerodynamic lens focuses aerosol with vacuum aerodynamic diameters between approximately 50 and

800 nm through a chopper and onto a vaporizer (~600° C). Upon vaporization, molecules undergo

electron impact ionization and the resulting ions are detected by a time of

fl

ight mass analyzer. A

pressure-controlled inlet maintained the sample

fl

ow rate at ~ 1.4 cm

−

to the AMS vacuum chamber.

The AMS ionization ef

fi

ciency (ratio of molecules ionizing relative to total molecules entering

instrument) was calibrated prior to

fl

ights using dried ammonium nitrate particles. Data are reported for

bulk aerosol based on ensemble average mass spectra. Spectra were analyzed in IGOR Pro (WaveMetrics,

Inc.) based on SQUIRREL and PIKA modules. Data were corrected for gas-phase interferences using a

fragmentation table

44,45

. Composition-dependent collection ef

fi

ciencies were quanti

fi

ed and applied using

a widely used approach

beginning with E-PEACE, while before that (MASE I/II) the collection

fi

ciency was estimated for each

fl

ight based on matching the total AMS mass to the mass determined

from the SMPS multiplied by the density derived from a comparison of size distributions form the AMS

and the SMPS. The two methods yield similar estimates of the collection ef

fi

ciency for particles measured

in this region

Water-soluble ionic composition was measured with a Particle-Into-Liquid Sampler (PILS; Brechtel

Manfucaturing Inc.) coupled to off-line ion chromatography (IC) analysis

. More speci

fi

cally, vials on a

rotating carousel collected samples every ~5 min, the contents of which were processed with IC after each

fl

ight. The PILS-IC technique speciated a suite of inorganic species (chloride, nitrite, bromide, nitrate,

Figure 1.

Spatial map summarizing

fl

ight tracks for each of the six

fi

eld campaigns.

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sulfate, sodium, ammonium, magnesium, calcium), amines (ethylamine, dimethylamine, diethylamine),

and organic acids (acetate, glycolate, formate, pyruvate, glyoxylate, maleate, oxalate, malonate, succinate,

glutarate, adipate, suberate, azelate, methanesulfonate). Three denuders were used to minimize biases

associated with acidic and basic inorganic gases, or with volatile organic compounds (VOCs). The

instrument

’

s droplet impactor plate was routinely cleaned between aircraft

fl

ights.

A focus during the 2015 BOAS campaign was on biological particles. A Model 4 Waveband Integrated

Bioaerosol Sensor (WIBS-4, DMT, Inc.) was deployed to detect and quantify primary biological aerosol

particle (PBAP) loading. WIBS-4 measures particle light scattering and auto

fl

uorescence of individual

particles with diameters between 0.5 and 16

μ

m. Particles are initially sized using the 90° side-scattering

signal from a 635 nm continuous-wave diode laser. The scattering intensity is directly related to particle

diameter, subject to Mie resonances as with the other optical probes; it was calibrated prior to

deployment using PSL calibration standards (0.8, 0.9, 1.0, 1.3, 2.0, 3.0

μ

m diameter, Thermo Scienti

fi

Inc.). WIBS-4 optical sizing is, therefore, based on the PSL refractive index of 1.59. Successive pulses of

Figure 2.

Illustration of two common

fl

ight strategies used to probe aerosol-cloud-precipitation-

meteorology interactions with the Twin Otter.

Figure 3.

Illustration of two

fl

ight strategies used to characterize ship plumes.

Blue lines represent the

fl

ight

track.

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